Abstract
The recent decade has seen a tremendous escalation of multimedia and its applications. These modern applications demand diverse security requirements and innovative security platforms. In this manuscript, we proposed an algorithm for image encryption applications. The core structure of this algorithm relies on confusion and diffusion operations. The confusion is mainly done through the application of the elliptic curve and S8 symmetric group. The proposed work incorporates three distinct chaotic maps. A detailed investigation is presented to analyze the behavior of chaos for secure communication. The chaotic sequences are then accordingly applied to the proposed algorithm. The modular approach followed in the design framework and integration of chaotic maps into the system makes the algorithm viable for a variety of image encryption applications. The resiliency of the algorithm can further be enhanced by increasing the number of rounds and S-boxes deployed. The statistical findings and simulation results imply that the algorithm is resistant to various attacks. Moreover, the algorithm satisfies all major performance and quality metrics. The encryption scheme can also resist channel noise as well as noise-induced by a malicious user. The decryption is successfully done for noisy data with minor distortions. The overall results determine that the proposed algorithm contains good cryptographic properties and low computational complexity makes it viable to low profile applications.
More Information
Identification Number: | https://doi.org/10.1140/epjp/s13360-020-00917-4 |
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Status: | Published |
Refereed: | Yes |
Publisher: | Editrice Compositori |
Additional Information: | This is a post-peer-review, pre-copyedit version of an article published in The European Physical Journal Plus. The final authenticated version is available online at: http://doi.org/10.1140/epjp/s13360-020-00917-4 |
Depositing User (symplectic) | Deposited by Abbas, Muhammad Azeem |
Date Deposited: | 11 Feb 2021 15:27 |
Last Modified: | 11 Jul 2024 15:45 |
Item Type: | Article |
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